Context-Based Spelling Correction for Japanese OCR
نویسنده
چکیده
We present a novel spelling correction method ['or those languages that have no delimiter between words, such ~rs ,lap;mese, (.',hinese, ,~nd ThM. It consists of an al)proximate word matching method and an N-best word seg mental|on Mgorithm using a statistical la.nguage model. For OCR errors, the proposed word-based correction method outperf.ornrs the conventional charactm'-b`ased correction method. When the bmselme character recognition accuracy is 90%, it achieves 96.0% character recognition accuracy and 96.3% word segmentation accuracy, while the cilar-acter recognition accuracy of cilaracter-b,ased correction is
منابع مشابه
Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model
We present a novel OCR error correction method for languages without word delimiters that have a large character set, such as Japanese and Chinese. It consists of a statistical OCR model, an approximate word matching method using character shape similarity, and a word segmentation algorithm using a statistical language model. By using a statistical OCR model and character shape similarity, the ...
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